7 citations · 17 across the 9 of their papers we have counts for
9 papers
CoRe-DA: Contrastive Regression for Unsupervised Domain Adaptation in Surgical Skill Assessment
Dimitrios Anastasiou, Razvan Caramalau, Jialang Xu +6
Vision-based surgical skill assessment (SSA) enables objective and scalable evaluation of operative performance. Progress in this field is constrained by the high cost and time dem…
Exploring Pre-training Across Domains for Few-Shot Surgical Skill Assessment
Dimitrios Anastasiou, Razvan Caramalau, Nazir Sirajudeen +11
Automated surgical skill assessment (SSA) is a central task in surgical computer vision. Developing robust SSA models is challenging due to the scarcity of skill annotations, which…
SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data
Xinwei Ju, Rema Daher, Razvan Caramalau +7
Improving the reliability and completeness of colonoscopic inspection is critical for reducing missed lesions and improving colorectal cancer prevention. Reliable scene understandi…
HUP-3D: A 3D multi-view synthetic dataset for assisted-egocentric hand-ultrasound pose estimation
Manuel Birlo, Razvan Caramalau, Philip J. "Eddie" Edwards +3
We present HUP-3D, a 3D multi-view multi-modal synthetic dataset for hand-ultrasound (US) probe pose estimation in the context of obstetric ultrasound. Egocentric markerless 3D joi…
Federated Active Learning for Target Domain Generalisation
Razvan Caramalau, Binod Bhattarai, Danail Stoyanov
In this paper, we introduce Active Learning framework in Federated Learning for Target Domain Generalisation, harnessing the strength from both learning paradigms. Our framework, F…
MoBYv2AL: Self-supervised Active Learning for Image Classification
Razvan Caramalau, Binod Bhattarai, Danail Stoyanov +1
Active learning(AL) has recently gained popularity for deep learning(DL) models. This is due to efficient and informative sampling, especially when the learner requires large-scale…
Visual Transformer for Task-aware Active Learning
Razvan Caramalau, Binod Bhattarai, Tae-Kyun Kim
Pool-based sampling in active learning (AL) represents a key framework for an-notating informative data when dealing with deep learning models. In this paper, we present a novel pi…
Active Learning for Bayesian 3D Hand Pose Estimation
Razvan Caramalau, Binod Bhattarai, Tae-Kyun Kim
We propose a Bayesian approximation to a deep learning architecture for 3D hand pose estimation. Through this framework, we explore and analyse the two types of uncertainties that…
Sequential Graph Convolutional Network for Active Learning
Razvan Caramalau, Binod Bhattarai, Tae-Kyun Kim
We propose a novel pool-based Active Learning framework constructed on a sequential Graph Convolution Network (GCN). Each image's feature from a pool of data represents a node in t…